In the search of potential epitopes for Wuhan seafood market pneumonia virus using high order nullomers

COVID-19 vaccine design using reverse and structural vaccinology, ontology-based literature mining and machine learning

Rational vaccine design, especially vaccine antigen identification and optimization, is critical to successful and efficient vaccine development against various infectious diseases including coronavirus disease 2019 (COVID-19). In general, computational vaccine design includes three major stages: (i) identification and annotation of experimentally verified gold standard protective antigens through literature mining, (ii) rational vaccine design using reverse vaccinology (RV) and structural vaccinology (SV) and (iii) post-licensure vaccine success and adverse event surveillance and its usage for vaccine design. Protegen is a database of experimentally verified protective antigens, which can be used as gold standard data for rational vaccine design. RV predicts protective antigen targets primarily from genome sequence analysis. SV refines antigens through structural engineering. Recently, RV and SV approaches, with the support of various machine learning methods, have been applied to COVID-19 vaccine design. The analysis of post-licensure vaccine adverse event report data also provides valuable results in terms of vaccine safety and how vaccines should be used or paused. Ontology standardizes and incorporates heterogeneous data and knowledge in a human- and computer-interpretable manner, further supporting machine learning and vaccine design. Future directions on rational vaccine design are discussed.

An immunological glimpse of human virus peptides: distance from self, MHC class I binding, Proteasome Cleveage, TAP Transport and sequence composition entropy

Adaptive immune response is triggered when specific pathogen peptides called epitopes are recognised as exogenous according to the paradigm of self/non-self. To be recognized by immune cells, epitopes have to be exposed (presented) on the surface of the cell. Predicting if a peptide is exposed is important to shed light on the rules that govern immune response, and thus to identify potential targets, and to design vaccine and drugs. We focused on peptides exposed on cell surface and made accessible to immune system through the MHC Class I complex. Before this can happen, three successive selection steps have to take place: a) Proteasome cleveage, b) TAP Transport, and c) binding to MHC-class I. Starting from a set of 211 host human reference viruses, we computed the set of unique peptides occurring in the correspondent proteomes. Then, we obtained the probability values of Proteasome Cleveage, TAP Transport and Binding to MHC Class I associated to those peptides through established prediction software tools. Such values were analysed in conjunction with two other features that could play a major role: the distance from self, strictly linked to the concept of nullomers, and the sequence entropy, measuring the complexity of the peptide amino acid composition. The analysis confirmed and extended previous results on a larger, more significant and consistent data set; we showed that the higher the distances from self, the higher the score of TAP Transport and binding to MHC class I; no significant association was instead found between distance from self and Proteasome Cleveage. Additionally, amino acid peptide composition entropy was significantly associated with the other features. In particular, higher entropies were linked with higher scores of Proteasome Cleveage, TAP Transport, Binding to MHC Class I, and higher distance from self. The relationship among the three selection steps provided evidence of a tight correlation among them, clearly suggesting it could be the product of a co-evolutive process. We believe that these results give new insights on the complex processes that regulate peptide presentation through MHC class I, and unveil the mechanisms the allow the immune system to distinguish self and viral non-self peptides.

Peptides for Vaccine Development

This review discusses peptide epitopes used as antigens in the development of vaccines in clinical trials as well as future vaccine candidates. It covers peptides used in potential immunotherapies for infectious diseases including SARS-CoV-2, influenza, hepatitis B and C, HIV, malaria, and others. In addition, peptides for cancer vaccines that target examples of overexpressed proteins are summarized, including human epidermal growth factor receptor 2 (HER-2), mucin 1 (MUC1), folate receptor, and others. The uses of peptides to target cancers caused by infective agents, for example, cervical cancer caused by human papilloma virus (HPV), are also discussed. This review also provides an overview of model peptide epitopes used to stimulate non-specific immune responses, and of self-adjuvanting peptides, as well as the influence of other adjuvants on peptide formulations. As highlighted in this review, several peptide immunotherapies are in advanced clinical trials as vaccines, and there is great potential for future therapies due the specificity of the response that can be achieved using peptide epitopes.

Computer simulation in the development of vaccines against covid-19 based on the hla-system antigens

The genetic variability of population may explain different individual immune responses to the SARS-CoV-2 virus. The use of genome- and peptidome-based technologies makes it possible to develop vaccines by optimizing the target antigens. The computer modeling methodology provides the scientific community with a more complete list of immunogenic peptides, including a number of new and cross-reactive candidates. Studies conducted independently of each other with different approaches provide a high degree of confidence in the reproducibility of results. Most of the effort in developing vaccines and drugs against SARS-CoV-2 is directed towards the thorn glycoprotein (protein S), a major inducer of neutralizing antibodies. Several vaccines have been shown to be effective in the preclinical studies and have been tested in the clinical trials to combat the COVID-19 infection. This review presents the profile of in silico predicted immunogenic peptides of the SARS-CoV-2 virus for the subsequent functional validation and vaccine development, and highlights the current advances in the development of subunit vaccines to combat COVID-19, taking into account the experience that has been previously achieved with SARS-CoV and MERS-CoV. The immunoinformatics techniques reduce the time and cost of developing vaccines that together can stop this new viral infection.

Persistent minimal sequences of SARS-CoV-2

Motivation

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused more than 14 million cases and more than half million deaths. Given the absence of implemented therapies, new analysis, diagnosis, and therapeutics are of great importance.

Results

Analysis of SARS-CoV-2 genomes from the current outbreak reveals the presence of short persistent DNA/RNA sequences that are absent from the human genome and transcriptome (PmRAWs). For the PmRAWs with length 12, only four exist at the same location in all SARS-CoV-2. At the gene level, we found one PmRAW of size 13 at the Spike glycoprotein coding sequence. This protein is fundamental for binding in human ACE2 and further use as an entry receptor to invade target cells. Applying protein structural prediction, we localized this PmRAW at the surface of the Spike protein, providing a potential targeted vector for diagnostics and therapeutics. Additionally, we show a new pattern of relative absent words (RAWs), characterized by the progressive increase of GC content (Guanine and Cytosine) according to the decrease of RAWs length, contrarily to the virus and host genome distributions. New analysis shows the same property during the Ebola virus outbreak. At a computational level, we improved the alignment-free method to identify pathogen-specific signatures in balance with GC measures and removed previous size limitations.

Availability and Implementation

https://github.com/cobilab/eagle.

Supplementary information

Supplementary data are available at Bioinformatics online.

Significant non-existence of sequences in genomes and proteomes

Minimal absent words (MAWs) are minimal-length oligomers absent from a genome or proteome. Although some artificially synthesized MAWs have deleterious effects, there is still a lack of a strategy for the classification of non-occurring sequences as potentially malicious or benign. In this work, by using Markovian models with multiple-testing correction, we reveal significant absent oligomers, which are statistically expected to exist. This suggests that their absence is due to negative selection. We survey genomes and proteomes covering the diversity of life and find thousands of significant absent sequences. Common significant MAWs are often mono- or dinucleotide tracts, or palindromic. Significant viral MAWs are often restriction sites and may indicate unknown restriction motifs. Surprisingly, significant mammal genome MAWs are often present, but rare, in other mammals, suggesting that they are suppressed but not completely forbidden. Significant human MAWs are frequently present in prokaryotes, suggesting immune function, but rarely present in human viruses, indicating viral mimicry of the host. More than one-fourth of human proteins are one substitution away from containing a significant MAW, with the majority of replacements being predicted harmful. We provide a web-based, interactive database of significant MAWs across genomes and proteomes.

The farther the better: Investigating how distance from human self affects the propensity of a peptide to be presented on cell surface by MHC class I molecules, the case of Trypanosoma cruzi

More than twenty years ago the reverse vaccinology paradigm came to light trying to design new vaccines based on the analysis of genomic information in order to select those pathogen peptides able to trigger an immune response. In this context, focusing on the proteome of Trypanosoma cruzi, we investigated the link between the probabilities for pathogen peptides to be presented on a cell surface and their distance from human self. We found a reasonable but, as far as we know, undiscovered property: the farther the distance between a peptide and the human-self the higher the probability for that peptide to be presented on a cell surface. We also found that the most distant peptides from human self bind, on average, a broader collection of HLAs than expected, implying a potential immunological role in a large portion of individuals. Finally, introducing a novel quantitative indicator for a peptide to measure its potential immunological role, we proposed a pool of peptides that could be potential epitopes and that can be suitable for experimental testing. The software to compute peptide classes according to the distance from human self is free available at http://www.iasi.cnr.it/~dsantoni/nullomers.

SARS-CoV-2 Vaccine Development: Current Status

In the midst of the severe acute respiratory syndrome coronavirus 2 pandemic and its attendant morbidity and mortality, safe and efficacious vaccines are needed that induce protective and long-lived immune responses. More than 120 vaccine candidates worldwide are in various preclinical and phase 1 to 3 clinical trials that include inactivated, live-attenuated, viral-vectored replicating and nonreplicating, protein- and peptide-based, and nucleic acid approaches. Vaccines will be necessary both for individual protection and for the safe development of population-level herd immunity. Public-private partnership collaborative efforts, such as the Accelerating COVID-19 Therapeutic Interventions and Vaccines mechanism, are key to rapidly identifying safe and effective vaccine candidates as quickly and efficiently as possible. In this article, we review the major vaccine approaches being taken and issues that must be resolved in the quest for vaccines to prevent coronavirus disease 2019. For this study, we scanned the PubMed database from 1963 to 2020 for all publications using the following search terms in various combinations: SARS, MERS, COVID-19, SARS-CoV-2, vaccine, clinical trial, coronavirus, pandemic, and vaccine development. We also did a Web search for these same terms. In addition, we examined the World Health Organization, Centers for Disease Control and Prevention, and other public health authority websites. We excluded abstracts and all articles that were not written in English.